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The 2nd ACM Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS) 2009
http://dsl.cs.uchicago.edu/MTAGS09/
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November 16th, 2009
Portland, Oregon, USA

Co-located with with IEEE/ACM International Conference for
High Performance Computing, Networking, Storage and Analysis (SC09)

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The 2nd workshop on Many-Task Computing on Grids and Supercomputers (MTAGS) will
provide the scientific community a dedicated forum for presenting new research,
development, and deployment efforts of loosely coupled large scale applications on
large scale clusters, Grids, Supercomputers, and Cloud Computing infrastructure.
Many-task computing (MTC), the theme of the workshop encompasses loosely coupled
applications, which are generally composed of many tasks (both independent and
dependent tasks) to achieve some larger application goal. This workshop will cover
challenges that can hamper efficiency and utilization in running applications on
large-scale systems, such as local resource manager scalability and granularity,
efficient utilization of the raw hardware, parallel file system contention and
scalability, reliability at scale, and application scalability. We welcome paper
submissions on all topics related to MTC on large scale systems. Papers will be
peer-reviewed, and accepted papers will be published in the workshop proceedings as
part of the ACM digital library. The workshop will be co-located with the
IEEE/ACM Supercomputing 2009 Conference in Portland Oregon on November 16th, 2009.
For more information, please visit http://dsl.cs.uchicago.edu/MTAGS09/.

Scope
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This workshop will focus on the ability to manage and execute large scale applications
on today's largest clusters, Grids, and Supercomputers. Clusters with 50K+ processor
cores are beginning to come online (i.e. TACC Sun Constellation System - Ranger), Grids
(i.e. TeraGrid) with a dozen sites and 100K+ processors, and supercomputers with 160K
processors (i.e. IBM BlueGene/P). Large clusters and supercomputers have traditionally
been high performance computing (HPC) systems, as they are efficient at executing
tightly coupled parallel jobs within a particular machine with low-latency
interconnects; the applications typically use message passing interface (MPI) to
achieve the needed inter-process communication. On the other hand, Grids have been the
preferred platform for more loosely coupled applications that tend to be managed and
executed through workflow systems. In contrast to HPC (tightly coupled applications),
these loosely coupled applications make up a new class of applications as what we call
Many-Task Computing (MTC). MTC systems generally involve the execution of independent,
sequential jobs that can be individually scheduled on many different computing
resources across multiple administrative boundaries. MTC systems typically achieve this
using various grid computing technologies and techniques, and often times use files to
achieve the inter-process communication as alternative communication mechanisms than
MPI. MTC is reminiscent to High Throughput Computing (HTC); however, MTC differs from
HTC in the emphasis of using many computing resources over short periods of time to
accomplish many computational tasks, where the primary metrics are measured in seconds
(e.g. FLOPS, tasks/sec, MB/s I/O rates). HTC on the other hand requires large amounts
of computing for longer times (months and years, rather than hours and days, and are
generally measured in operations per month).

Today's existing HPC systems are a viable platform to host MTC applications. However,
some challenges arise in large scale applications when run on large scale systems,
which can hamper the efficiency and utilization of these large scale systems. These
challenges vary from local resource manager scalability and granularity, efficient
utilization of the raw hardware, shared file system contention and scalability,
reliability at scale, application scalability, and understanding the limitations of the
HPC systems in order to identify good candidate MTC applications. Furthermore, the MTC
paradigm can be naturally applied to the emerging Cloud Computing paradigm due to its
loosely coupled nature, which is being adopted by industry as the next wave of
technological advancement to reduce operational costs while improving efficiencies in
large scale infrastructures.

For an interesting discussion in a blog by Ian Foster on the difference between MTC and
HTC, please see his blog at http://ianfoster.typepad.com/blog/2008/07/many-tasks-comp.html.
We also published two papers that are highly relevant to this workshop. One paper is
titled "Toward Loosely Coupled Programming on Petascale Systems", and was published in
SC08; the second paper is titled "Many-Task Computing for Grids and Supercomputers",
which was published in MTAGS08. Furthermore, to see last year's workshop program agenda,
and accepted papers and presentations, please see http://dsl.cs.uchicago.edu/MTAGS08/.
For more information, please visit http://dsl.cs.uchicago.edu/MTAGS09/.

Topics
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MTAGS 2008 topics of interest include, but are not limited to:
* Compute Resource Management in large scale clusters, large Grids, Supercomputers,
or Cloud Computing infrastructure
o Scheduling
o Job execution frameworks
o Local resource manager extensions
o Performance evaluation of resource managers in use on large scale systems
o Challenges and opportunities in running many-task workloads on HPC systems
o Challenges and opportunities in running many-task workloads
on Cloud Computing infrastructure
* Data Management in large scale Grid and Supercomputer environments:
o Data-Aware Scheduling
o Parallel File System performance and scalability in large deployments
o Distributed file systems
o Data caching frameworks and techniques
* Large-Scale Workflow Systems
o Workflow system performance and scalability analysis
o Scalability of workflow systems
o Workflow infrastructure and e-Science middleware
o Programming Paradigms and Models
* Large-Scale Many-Task Applications
o Large-scale many-task applications
o Large-scale many-task data-intensive applications
o Large-scale high throughput computing (HTC) applications
o Quasi-supercomputing applications, deployments, and experiences

Paper Submission and Publication
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Authors are invited to submit papers with unpublished, original work of not more than
10 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages,
as per ACM 8.5 x 11 manuscript guidelines
(http://www.acm.org/publications/instructions_for_proceedings_volumes); document
templates can be found at http://www.acm.org/sigs/publications/proceedings-templates.
A 250 word abstract (PDF format) must be submitted online at
https://cmt.research.microsoft.com/MTAGS2009/ before the deadline of August 1st, 2009
at 11:59PM PST; the final 10 page papers in PDF format will be due on September 1st,
2009 at 11:59PM PST. Papers will be peer-reviewed, and accepted papers will be
published in the workshop proceedings as part of the ACM digital library. Notifications
of the paper decisions will be sent out by October 1st, 2009. Selected excellent work
will be invited to submit extended versions of the workshop paper to the
IEEE Transactions on Parallel and Distributed Systems (TPDS) Journal, Special Issue on
Many-Task Computing (due December 21st, 2009); for more information about this journal
special issue, please visit http://dsl.cs.uchicago.edu/TPDS_MTC/. Submission implies
the willingness of at least one of the authors to register and present the paper. For
more information, please visit http://dsl.cs.uchicago.edu/MTAGS09/.

Important Dates
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* Abstract Due: August 1st, 2009
* Papers Due: September 1st, 2009
* Notification of Acceptance: October 1st, 2009
* Camera Ready Papers Due: November 1st, 2009
* Workshop Date: November 16th, 2009



Committee Members
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Workshop Chairs
* Ioan Raicu, University of Chicago
* Ian Foster, University of Chicago & Argonne National Laboratory
* Yong Zhao, Microsoft

Technical Committee (confirmed)
* David Abramson, Monash University, Australia
* Pete Beckman, Argonne National Laboratory, USA
* Peter Dinda, Northwestern University, USA
* Ian Foster, University of Chicago & Argonne National Laboratory, USA
* Bob Grossman, University of Illinois at Chicago, USA
* Indranil Gupta, University of Illinois at Urbana Champaign, USA
* Alexandru Iosup, Delft University of Technology, Netherlands
* Kamil Iskra, Argonne National Laboratory, USA
* Chuang Liu, Ask.com, USA
* Zhou Lei, Shanghai University, China
* Shiyong Lu, Wayne State University, USA
* Reagan Moore, University of North Carolina at Chapel Hill, USA
* Marlon Pierce, Indiana University, USA
* Ioan Raicu, University of Chicago, USA
* Matei Ripeanu, University of British Columbia, Canada
* David Swanson, University of Nebraska, USA
* Greg Thain, Univeristy of Wisconsin, USA
* Matthew Woitaszek, The University Corporation for Atmospheric Research, USA
* Sherali Zeadally, University of the District of Columbia, USA
* Yong Zhao, Microsoft, USA